769 results about "Digital video" patented technology

The invention provides a multi-target tracking detection method and system based on cascade matching and trajectory confirmation, and relates to the technical field of digital video monitoring and tracking, and the method comprises the steps: obtaining a personnel construction video, and decomposing a video frame into a plurality of images; identifying a target in the current frame of image based on an improved YOLOv5 network, obtaining a target detection frame, and obtaining a prediction trajectory frame of the current frame through a Kalman filtering algorithm based on the trajectory frame of the previous frame; performing multi-target tracking on the target detection frame and the prediction trajectory frame of the current frame by using a DeepSort algorithm, respectively obtaining motion features and appearance features of the target detection frame and the prediction trajectory frame, performing cascade matching on the motion features and the appearance features of the target detection frame and the prediction trajectory frame by using a Hungary algorithm, and performing matching optimization by using an IOU matching algorithm; and carrying out fusion updating on the successfully matched target detection frame and prediction trajectory frame by using a Kalman filtering algorithm, and replacing the original prediction trajectory frame to obtain a tracking result.

Devices, systems, and methods for encoding and decoding digital video using a lookup table (LUT) containing motion candidates are described. In a representative aspect, a method of video processing includes: maintaining one or more tables, wherein at least one of the one or more tables is associated with one or more entries; deriving a second set of motion candidates based on a first set of motion candidates in the at least one table; and performing a conversion between a current block of a video and a bitstream representation of the video based on the second set of motion candidates.

The invention discloses a short video editing synthesis method based on fuzzy logic. The method comprises the following steps: S1, carrying out digital video preprocessing on an input original short video; s2, forming a short video feature data set; s3, generating a fuzzy logic decision result; s4, performing multi-target and multi-parameter optimization on the fuzzy logic decision result by adopting a random score programming method to form an optimized editing parameter set; s5, generating a preliminarily synthesized short video; s6, generating a video quality evaluation result; and S7, carrying out iterative optimization on the preliminarily synthesized short video according to a video quality evaluation result, adjusting the editing parameters and re-executing the editing synthesis step until the video quality evaluation result meets a preset standard, and generating a final edited finished product. According to the method, the editing scheme can achieve the best balance in the aspects of visual rhythm, information integrity and emotion expression consistency.

This item is a digital video camera used for cinema shooting and the like with interchangeable lenses.

The invention belongs to the technical field of computer vision and digital video processing, and discloses a video object segmentation method based on query adaptive attention and discriminative memory, which comprises the following steps: step 1, constructing a video data set and preprocessing data; step 2, constructing a video object segmentation model combining multi-scale semantic feature integration and query adaptive discriminant enhancement, and training the video object segmentation model; step 3, video object segmentation reasoning; performing target segmentation reasoning on the preprocessed video sequence, outputting a frame-by-frame target segmentation mask, and generating a time sequence tracking result; 4, exporting, deploying and applying the model; through lightweight network design and a discriminative memory optimization strategy, the model is deployed to edge equipment, and real-time segmentation and visualization are realized. According to the method, on one hand, comprehensive target representation is provided on multi-scale feature extraction, and on the basis of the characteristic that only high-confidence target features are stored, error propagation is avoided, and the long-term segmentation stability of the method is ensured.

The present disclosure relates to systems, non-transitory computer-readable media, and methods for capturing snapshots of digital content displayed on a client device and searching through the captured content. The disclosed systems provide a search function for effectively traveling back in time to identify digital content previously displayed on a client device. The disclosed systems provide options for capturing snapshots of content displayed on a display screen, extracting data from the snapshots, and storing the snapshots for use when populating search results. The disclosed systems utilize machine learning models to extract text and / or to generate text versions of snapshots including extracted text, descriptions of images, transcripts of videos, and / or textual summaries from displayed documents or webpages. In response to a search query, the disclosed systems can produce search results that include digital videos including captured snapshots of content displayed by a client device over time.

Devices, systems, and methods for digital video coding, which includes matrix-based intra prediction methods for video coding, are described. In a representative aspect, a method for video processing includes performing a conversion between a current video block of a video and a bitstream representation of the current video block according to a rule, where the rule specifies a relationship between applicability of a matrix based intra prediction (MIP) mode or a transform mode during the conversion, where the MIP mode includes determining a prediction block of the current video block by performing, on previously coded samples of the video, a boundary downsampling operation, followed by a matrix vector multiplication operation, and selectively followed by an upsampling operation, and where the transform mode specifies use of a transform operation for the determining the prediction block for the current video block.

Methods and systems for mapping video conferencing content to video frames are provided. In an example method, a processing device receives video conference information and a digital video, the digital video including a plurality of frames. The processing device segments the video conference information into one or more video-conference time segments and the digital video into one or more digital-video time segments. The processing device associates each video-conference time segment with a digital-video time segment. The processing device maps first content information of a first video-conference time segment of the one or more video-conference time segments onto a first digital-video time segment associated with the first video-conference time segment based a first identifier of the first content information. The processing device causes the first content information to be displayed during a displaying of the digital video.

A transmitter includes a distributor that receives a stream of digital video samples and distributes these samples into vectors in a buffer per a permutation. A digital-to-analog converter (DAC) per vector receives from its corresponding vector the digital video samples and converts the digital video samples into analog video samples. Each source driver includes a collector that receives analog video samples from each DAC and stores the analog video samples of the corresponding vector, and amplifiers that receive the stored analog video samples in parallel from the collector and amplifies the stored analog video samples onto a column of the display panel. An AR / VR headset uses analog video transport to its processor, and from the processor to a display of the visor. Analog video transport is used between a camera and processor and between processor and display. Analog video is transmitted to or within the headset wired or wirelessly.

The invention discloses a high-quality cultural relic digital video three-dimensional reconstruction method and system, and the method comprises the steps: obtaining the video data of a cultural relic, and enabling the video data to comprise a frame image under a time sequence; obtaining a relative pose of the frame image, wherein the relative pose is a camera pose of each frame image relative to the first frame image; segmenting the frame image to obtain segments, and sharing a plurality of front frame images and a plurality of rear frame images in the segments with a front segment and a rear segment respectively; generating corresponding Gaussian ellipsoid distribution according to each segment; and combining the Gaussian ellipsoid distribution to obtain final Gaussian ellipsoid distribution, namely a three-dimensional model of the cultural relic.

The invention relates to the technical field of digital video devices, in particular to a digital video device control method and device. The method comprises the following steps: acquiring digital monitoring data, performing real-time scene acquisition and dynamic region optimization according to the data, and generating optimized dynamic region data; video frames are read based on the dynamic region optimization data, and abnormal behavior analysis and behavior intention evaluation are carried out; calculating the complexity of monitoring behaviors by combining video frame data and behavior intention data, and evaluating resource consumption increase; the processing bottleneck is evaluated according to the resource consumption growth data, and the processing capability attenuation analysis is carried out, so that the monitoring device is adjusted, and the system performance is optimized; according to the method, the resource allocation and processing capability of the video device is dynamically adjusted through real-time analysis and processing of monitoring data. According to the invention, the digital video device is adjusted, so that the prediction identification of the digital video device is more accurate and efficient.

Devices, systems and methods for digital video coding, which includes matrix-based intra prediction methods for video coding, are described. In a representative aspect, a method for video processing includes performing a conversion between a current video block of a video and a bitstream representation of the current video block according to a rule, where the rule specifies a relationship between applicability of a matrix based intra prediction (MIP) mode or a transform mode during the conversion, where the MIP mode includes determining a prediction block of the current video block by performing, on previously coded samples of the video, a boundary downsampling operation, followed by a matrix vector multiplication operation, and selectively followed by an upsampling operation, and where the transform mode specifies use of a transform operation for the determining the prediction block for the current video block.

The present disclosure relates to systems, methods, and non-transitory computer-readable media that learns parameters for a natural language video localization model utilizing a curated dataset. In particular, in some embodiments, the disclosed systems generate a set of similarity scores between a target query and a video dataset that includes a plurality of digital videos. For instance, the disclosed systems determines a false-negative threshold by utilizing the set of similarity scores to exclude a subset of false-negative samples from the plurality of digital videos. Further, the disclosed systems determines a negative sample distribution and generates a curated dataset that includes a subset of negative samples with the subset of false-negative samples excluded.

Digital video editing techniques are described that are based on a target digital image. In one or more implementations, inputs are received. The inputs include a target text prompt, a target digital image depicting a target object, and a source digital video having a plurality of frames depicting a source object. Regions-of-interest are identified in the plurality of frames of the source digital video, respectively, based on the target text prompt and the target digital image using a machine-learning model, e.g., a diffusion model. A plurality of frames of a target digital video are generated as having the target object using a generative machine-learning model. The generating is based on the regions-of-interest, the target digital image, the source digital video, and a source text prompt describing the source digital video.

The present disclosure relates to systems, methods, and non-transitory computer-readable media for segmenting a digital video to segment a digital video by employing a chapterization approach to video transcripts based on contextual data from audio signals and video signals together. In some embodiments, the disclosed systems can extract various types of audio signals and various types of video signals from a digital video. From the extracted signals, the disclosed systems can determine a set of break points to segment a video transcript. In some embodiments, the disclosed systems can further recommend, via a notification on a client device, inserting corresponding breaks from the segmented transcript into the digital video.

Method, system and computer program product for providing an output digital video stream, comprising:continuously collecting a real-time first primary digital video stream;performing a first digital image analysis of the first primary digital video stream to identify at least one first event or pattern, resulting in a first production control parameter being established at a first time delay in relation to a time of occurrence of said first event or pattern in the first primary digital video stream;applying said first production control parameter to said first primary digital video stream, resulting in the first primary digital video stream being modified without being delayed by said first time delay, so as to produce a first produced digital video stream; and continuously providing said output digital video stream based on said first produced digital video stream.

The invention relates to digital video image processing. In particular, the invention provides methods, systems and computer program products that optimize processes for generation of high dynamic range output video streams by optimizing the processes of parsing or extracting information from multiple input image frames and combining the multiple input image frames into a composite high dynamic range output video frames.

Disclosed herein are systems and method for curating and distributing digital content; including: digital video, music, pictures, etc. For example, presented herein are systems and methods for providing a digital content program, including a plurality of continuously provided digital assets streamed over a digital content platform. Example embodiments include: (a) curating a plurality of assets; (b) selecting a subset of assets from the plurality of assets, based on similarity metrics between assets; and (c) ordering the subset of assets into a digital content program.

The embodiment of the invention provides a digital video monitoring data transmission synchronization method and system, and relates to the technical field of digital video monitoring data transmission synchronization, and the method comprises the steps: receiving a video data stream and an external sensor data stream which is related to the content of the video data stream and has an independent stable time synchronization mechanism; identifying a visual event from the video data stream, and identifying a physical event associated with the visual event from the external sensor data stream; taking the timestamp of the physical event as a time anchor point, obtaining a visual original timestamp of the visual event, and calculating the time deviation of the video data stream according to the time anchor point and the visual original timestamp; based on the time deviation, correcting the frame timestamp of the video data stream by adopting an adaptive weighted average or filtering strategy to obtain a corrected timestamp; and fusing the corrected timestamps to obtain a global time reference. The reliability of the monitoring data and the accuracy of the analysis result can be improved.

One variation of a method includes, during a pause event that pauses playback of a digital video rendered within a display of a primary device: triggering playback of a video advertisement rendered in replacement of the digital video during the pause event; and, during playback of the video advertisement, rendering a digital identifier within the display, the digital identifier including a pointer to an electronic document including content associated with the video advertisement. The method further includes, during playback of the video advertisement, in response to a scan event that captures the digital identifier and initiated at a secondary device distinct from the primary device: pausing playback of the video advertisement at the primary device; triggering playback of the digital video, in replacement of the video advertisement, at the primary device; and triggering the secondary device to navigate to the electronic document based on the pointer.

One variation of a method for serving interactive content to a user includes, at a visual element inserted into a document accessed by a computing device: loading a first frame from a digital video; in response to a scroll-down event that moves the visual element upward from a bottom of a window rendered on the computing device toward a top of the window, seeking from the first frame through a subset of frames in the digital video in a first direction at a rate corresponding to a scroll rate of the scroll-down event, the subset of frames spanning a duration of the digital video corresponding to a length of the scroll-down event; and, in response to termination of the scroll-down event with the visual element remaining in view within the window, playing the digital video forward from a last frame in the subset of frames in the digital video.

An archive model can be used for managing networked storage of recorded content, such as network DVR (digital video recorder) content. Content may be initially recorded to an active storage device, with individual duplicate copies recorded for each requesting user, and subsequently archived to an archive storage device. For playback, the content can be reconstituted into the active storage device prior to delivery to the requesting user. Content can be predictively reconstituted in anticipation of user needs, and the reconstitution capacity of the system can be dynamically reallocated for load balancing.

Devices, systems and methods for digital video coding, which includes matrix-based intra prediction methods for video coding, are described. In a representative aspect, a method for video processing includes performing a first determination whether a luma video block of a video is coded using a matrix based intra prediction (MIP) mode; performing a second determination that the luma video block is applicable for determining a chroma intra mode for a current chroma video block of the video; performing, based on the first determination and the second determination, a third determination about the chroma intra mode to be used for the current chroma video block; and performing, based on the third determination, a conversion between the current chroma video block and a bitstream representation of the current chroma video block.

Disclosed herein are methods, systems, and computer-readable media for training a machine learning model to label unlabeled data and / or perform automated actions. In an embodiment, a method comprises receiving unlabeled digital video data, generating pseudo-labels for the unlabeled digital video data, the generating comprising receiving labeled digital video data, training an inverse dynamics model (IDM) using the labeled digital video data, and generating at least one pseudo-label for the unlabeled digital video data, wherein the at least one pseudo-label is based on a prediction, generated by the IDM, of one or more actions that mimic at least one timestep of the unlabeled digital video data. In some embodiments, the method further comprises adding the at least one pseudo-label to the unlabeled digital video data and further training the IDM or a machine learning model using the pseudo-labeled digital video data.

The invention discloses an adaptive video restoration method based on a digital video technology, and relates to the technical field of image communication. The method comprises the following steps: preprocessing an original video containing hard subtitles and automatically removing the hard subtitles to obtain a video to be repaired; screening a reference frame and a to-be-repaired frame by comparing the original video with the to-be-repaired video; determining a to-be-repaired area according to the pixel gray scale difference; extracting matched feature points, calculating a reference motion vector, estimating possible positions and motion differences of points in the to-be-repaired region in combination with object structure segmentation and region prediction, and generating a corrected motion vector; performing sub-pixel-level interpolation by using the vector, and constructing a corrected reference image; and finally, fusing the corrected image and the to-be-repaired area to generate a repaired video frame. The method can effectively improve the restoration quality of the subtitle shielded area.

A wearable digital video camera (10) is equipped with wireless connection protocol and global navigation and location positioning system technology to provide remote image acquisition control and viewing. The Bluetooth® packet-based open wireless technology standard protocol (400) is preferred for use in providing control signals or streaming data to the digital video camera and for accessing image content stored on or streaming from the digital video camera. The GPS technology (402) is preferred for use in tracking of the location of the digital video camera as it records image information. A rotating mount (300) with a locking member (330) on the camera housing (22) allows adjustment of the pointing angle of the wearable digital video camera when it is attached to a mounting surface.

The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize machine learning to generate a sequence of transition frames for a gap in a clipped digital video. For example, the disclosed system receives a clipped digital video that includes a pre-cut frame prior to a gap in the clipped digital video and a post-cut frame following the gap in the clipped digital video. Moreover, the disclosed system utilizes a natural motion sequence model to generates a sequence of transition keypoint maps between the pre-cut frame and the post-cut frame. Furthermore, using a generative neural network, the disclosed system generates a sequence of transition frames for the gap in the clipped digital video from the sequence of transition keypoint maps.

A transmitter includes a distributor that receives a stream of digital video samples and distributes the digital video samples into vectors in a buffer per a permutation. A digital-to-analog converter (DAC) per vector receives from its corresponding vector the digital video samples and converts the digital video samples into analog video samples. Each source driver includes a collector that receives analog video samples from each DAC and stores the analog video samples of the corresponding vector, and amplifiers that receive the stored analog video samples in parallel from the collector and amplifies the stored analog video samples onto a column of the display panel. Synchronization uses modified MFM and sample phase alignment. The source drivers are integrated with the substrate of the display panel using transistors. An AR / VR headset uses analog video transport between processor and visor and transmits and receives wirelessly.

Systems, apparatus, and methods for post-processing video e.g. frame denoising. Noise reduction techniques may be employed to improve the quality of digital video. Frames may be extracted from a video. Synthetic frames may be created using motion data between the extracted frames. Synthetic frames may be masked to exclude pixels from the composite frame. Thresholds used in masking may vary based on the temporal distance of the extracted frame used to create the synthetic frame and the extracted frame. Masking may be based on frame differences between extracted and synthetic frames (e.g., sub-pixel / luminance differences), areas of lower quality motion data (e.g., occlusions), or edge detection in the extracted frames. Synthetic and extracted frames may be composited generating frames having less noise. The composited frame may be based on averaging pixel values across the synthetic and extracted frames. Composited frames may be compiled and encoded into denoised video.

The invention discloses a high-definition real-time digital video monitoring system for realizing abnormal behavior recognition, relates to the technical field of communication, and solves the technical problem of improving the abnormal behavior recognition capability. The system comprises a video acquisition module, a preprocessing module, an analysis module, an abnormity determination module, an alarm module, a storage management module and a dynamic interaction module. According to the invention, the dynamic range of video acquisition is optimized through a quantum dot sensor array technology and an ambient light adaptive adjustment technology, multi-target detection tracking is realized through a YOLOv5 algorithm and a DeepSORT algorithm, and behavior characteristics are extracted in combination with a space-time diagram convolutional network. And through a rule and lightweight deep learning abnormity determination module, the identification accuracy is improved so as to ensure stable operation and real-time response capability in a complex scene. And the real-time identification capability of the digital video is greatly improved.